A generalized power iteration method for solving quadratic problem on the Stiefel manifold

被引:0
作者
Feiping Nie
Rui Zhang
Xuelong Li
机构
[1] Northwestern Polytechnical University,School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL)
[2] Chinese Academy of Sciences,Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics
来源
Science China Information Sciences | 2017年 / 60卷
关键词
quadratic problem; Stiefel manifold; power iteration; procrustes problem; orthogonal least square regression;
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中图分类号
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摘要
In this paper, we first propose a novel generalized power iteration (GPI) method to solve the quadratic problem on the Stiefel manifold (QPSM) as minWTW=I\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$min_{W^{T}W=I}$$\end{document} Tr(WTAW − 2WTB) along with the theoretical analysis. Accordingly, its special case known as the orthogonal least square regression (OLSR) is under further investigation. Based on the aforementioned studies, we then majorly focus on solving the unbalanced orthogonal procrustes problem (UOPP). As a result, not only a general convergent algorithm is derived theoretically but the efficiency of the proposed approach is verified empirically as well.
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